Evaluation of Different Wind Fields for Storm Surge Modeling in the Persian Gulf

With the increasing demand for accurate storm-surge predictions in coastal regions, there is an urgent need to select the most accurate wind field product to use in hydrodynamic prediction models. In this study, the responses of a coastal and ocean circulation model to four wind products, QuikSCAT, European Center of Middle-Range Weather Forecasting (ECMWF) ERA-Interim, Global Forecast System (GFS), and Cross-Calibrated Multi-Platform (CCMP), were evaluated. Simulation of water-level fluctuation with the mentioned wind forcings were compared with tide-gauge observations in the northern part of the Persian Gulf. The results show that using the GFS wind field, which is a global numerical weather prediction model, produces better results compared with using other wind datasets. Although the result shows competitive improvement of the storm-surge prediction between the GFS and the CCMP forced model, the former exceeds the results almost in all stations. The correlation coefficient of the GFS-forced model for Kangan tide-gauge station is 0.80 compared with those of QuikSCAT, ECMWF, and CCMP, which are 0.64, 0.73, and 0.79, respectively.